Nationwide autonomous ridepooling in Germany: a large-scale agent-based transport simulation and external cost assessment

Abstract

Autonomous vehicles are widely expected to generate substantial social, environmental, and economic benefits. However, these anticipated effects are still largely derived from simulations, models, and forecasts, which have so far focused predominantly on dense urban settings. This emphasis leaves an important gap, as autonomous vehicles deployed as a shared and pooled mobility service may be particularly valuable for improving accessibility and mobility in suburban and rural areas, where such benefits have rarely been assessed. Building on empirical mobile-phone origin–destination flows, this study presents the first agent-based simulation of an autonomous ridepooling system at a nationwide scale. The model represents a service operating across all of Germany, serving nearly 12 million daily rides with a fleet of 300,000 vehicles, and evaluates its implications for users, operators, and society. The results indicate a pooling rate of 77%, a mean vehicle occupancy of 1.67, and an average waiting time of 10 minutes. In addition, the system is estimated to reduce external transport costs by 3.6 billion euros annually. These findings suggest that, if effectively implemented, autonomous ridepooling could deliver substantial individual, societal, and environmental benefits not only in cities but across an entire country.